• 대기
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• 제25권2호
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• pp.309-322
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• 2015

The objective of this study is to evaluate the impact of the high resolution topographies and landuses data on simulated meteorological variables (wind speed at 10 m, temperature at 2 m and relative humidity at 2 m) in WRF. We compare the results with WRF simulation using each resolution of the topographies and landuses, and with 37 AWS observation data on the Seoul metropolitan regions. According to results of using high-resolution topography, WRF model gives better topographical expression over domain. And we can separate more detail (Low intensity residential, high intensity residential, industrial or commercial) using high resolution landuses data. The result shows that simulated temperature and wind speed are generally higher than AWS observation data. However, simulation trend with temperature, wind speed, and relative humidity are similar to observation data. The reason for that is that the high precipitation event occurred in CASE 1 and 2. Temperature have correlation of 0.43~0.47 and standard deviation of $2.12{\sim}2.28^{\circ}C$ in CASE 1, while correlation of more than 0.8 and standard deviation of $3.05{\sim}3.18m\;s^{-1}$ in CASE 2. In case of wind speed, correlation have lower than 0.5 and Standard Deviation of $1.88{\sim}2.34m\;s^{-1}$ in CASE 1 and 2. In statistical analysis shows that using highest resolution (U01) results are more close to the AWS observation data. It can be concluded that the topographies and landuses are important factor that affect model simulation. However, the tendency to always use high resolution topographies and landuses data appears to be unjustified, and optimal solution depends on the combination of scale effect and mechanisms of dynamic models.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2002년도 유체기계 연구개발 발표회 논문집
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• pp.363-369
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• 2002

Orifice meter is the most widely used flowmeter in custody transfer between KOGAS and city gas companies. Absolute pressure value is needed to calculate the gas flow of orifice metering system, but the gauge pressure transmitters are mainly used in the field. In case that the gauge pressure transmitters are used, the fixed value as standard atmospheric pressure(101.325kPa) is applied for the absolute pressure value. The real, local atmospheric pressures of each metering station are different from the standard condition as the altitude and weather conditions. In this study the flow calculation errors were quantitatively analyzed through examining the atmospheric pressures of 50 stations of KOGAS. The data for analysis are such like the time data of supplied gas amount, the altitude of each metering station, the time data of atmospheric pressures and altitudes of each weather observatory. The results showed that the local atmospheric pressures were different from the standard value and the gas flow calculation errors were distributed between $-0.024\%{\~}0.025\%$ based on the supplied gas amount in the year 1999 and 2000.

• 한국조경학회지
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• 제21권4호
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• pp.69-82
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• 1994

The purpose of this study is to estimate the probable period of the planting work in consideration of weather factors. The impact degree of weather factors on the control of planting schedule was measured by the possible working days on the basis of weather condition. To establish the weather standard, the researcher analyzed the questionnaires on the manager of planting work and also the meteorological data for 10 years(1983-1992) in Seoul. The results are as follows; $\circled1$ The possible period of the planting work is from March 17 to May 18 Spring and from September 26 to December 15 in Autumn during a year. $\circled2$ The problem working days of the planting work(106-130) days per year) are less than the building construction days(174 days per year), because of handling the living material of plants, specially in summer and winter.

• 대기
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• 제26권3호
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• pp.461-471
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• 2016

A quality check algorithm for the Weather Information Service Engine pulsed Doppler wind lidar is developed from a view point of spatial and temporal consistencies of observed wind speed. Threshold values for quality check are determined by statistical analysis on the standard deviation of 3-component of wind speed obtained by a wind lidar, and the vertical gradient of horizontal wind speed obtained by a radiosonde system. The algorithm includes carrier-to-noise ratio (CNR) check, data availability check, and vertical gradient of horizontal wind speed check. That is, data sets whose CNR is less than -29 dB, data availability is less than 90%, or vertical gradient of horizontal wind speed is less than $-0.028s^{-1}$ or larger than $0.032s^{-1}$ are classified as 'doubtful', and flagged. The developed quality check algorithm is applied to data obtained at Bucheon station for the period from 1 to 30 September 2015. It is found that the number of 'doubtful' data shows maxima around 2000 m high, but the ratio of 'doubtful' to height-total data increases with increasing height due to atmospheric boundary height, cloud, or rainfall, etc. It is also found that the quality check by data availability is more effective than those by carrier to noise ratio or vertical gradient of horizontal wind speed to remove an erroneous noise data.

• Smart Structures and Systems
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• 제34권1호
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• pp.9-15
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• 2024

Oversampling algorithms are methods employed in the field of machine learning to address the constraints associated with data quantity. This study aimed to explore the variations in reliability as data volume is progressively increased through the use of oversampling algorithms. For this purpose, the synthetic minority oversampling technique (SMOTE) and the borderline synthetic minority oversampling technique (BSMOTE) are chosen. The data inputs, which included air temperature, humidity, and wind speed, are parameters used in the Fosberg Fire-Weather Index (FFWI). Starting with a base of 52 entries, new data sets are generated by incrementally increasing the data volume by 10% up to a total increase of 100%. This augmented data is then utilized to predict FFWI using a deep neural network. The coefficient of determination (R²) is calculated for predictions made with both the original and the augmented datasets. Suggesting that increasing data volume by more than 50% of the original dataset quantity yields more reliable outcomes. This study introduces a methodology to alleviate the challenge of establishing a standard for data augmentation when employing oversampling algorithms, as well as a means to assess reliability.

• 한국항해항만학회지
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• 제35권3호
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• pp.265-270
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• 2011

본 연구는 건물에너지 효율 향상을 위한 목적으로 기상데이터 변화에 따른 건물 냉 난방부하량을 예측하고 결과를 비교 분석한 것으로, 연구 성과는 다음과 같다. 1)기상청에서 입수데이터를 평가툴인 ESP-r에 활용할 수 있도록 항목별 기상데이터를 개발하였다. 표준기상 데이터의 외기온도, 습도, 풍속은 대부분의 경우 기상청데이터 보다 크거나 높았다. 수평면전일사량은 기상청데이터가 높았고, 직달일사량은 겨울철에는 표준기상데이터가, 여름철에는 기상청데이터가 많은 것으로 나타났다. 2)대학교 캠퍼스 내에 신축된 후생복지관을 대상으로 한 시뮬레이션 결과, 최대난방부하의 경우 표준년도, 2006년, 2009년이 비슷한 반면 2007년은 표준년도 대비 81%, 2008년은 96% 수준이었고, 연간난방부하는 2006년, 2008년의 순으로 난방수요가 많았다. 한편, 냉방부하의 경우에는, 상대적으로 최대냉방부하가 큰 2007년, 2009년의 연간 냉방부하보다 최대냉방부하가 가장 적은 2008년의 연간냉방부하가 더 큰 결과를 보였다. 3)냉 난방기기의 상당시간가동률을 평가한 결과, 표준년도의 최대부하대비 상당시간가동률은 2006~2009년이 표준년도에 비해 대부분 가동률이 낮았다.

• 신재생에너지
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• 제20권1호
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• pp.95-101
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• 2024

Since 1990, the Renewable Big Data Research Lab at the Korea Institute of Energy Technology has been observing solar radiation at 16 sites across South Korea. Serving as the National Reference Standard Data Center for Renewable Energy since 2012, it produces essential data for the sector. By 2020, it standardized meteorological year data from 22 sites. Despite user demand for data from approximately 260 sites, equivalent to South Korea's municipalities, this need exceeds the capability of measurement-based data. In response, our team developed a method to derive solar radiation data from satellite images, covering South Korea in 400,000 grids of 500 m × 500 m each. Utilizing satellite-derived data and ERA5-Land reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), we produced standard meteorological year data for 1,000 sites. Our research also focused on data measurement traceability and uncertainty estimation, ensuring the reliability of our model data and the traceability of existing measurement-based data.

• Water Engineering Research
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• 제3권2호
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• pp.113-122
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict flash floods. In this study, a Quantitative Flood Forecasting (QFF) model was developed by incorporating the evolving structure and frequency of intense weather systems and by using neural network approach. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as lifetime, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. All these processes stretched leadtime up to 18 hours. The QFF model will be applied to the mid-Atlantic region of United States in a forthcoming paper.

• 대한원격탐사학회지
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• 제15권1호
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• pp.9-20
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• 1999

농업을 비롯한 산업활동을 효율적으로 수행하기 위해서는 전문 기상정보의 활용이 필수적이다. 영농활동에 있어서 의사지원시스템의 핵심으로 떠오르고 있는 작물 생장모형은 부단히 변화하는 대기환경에 대한 공간정보를 요구하기 때문에, 모형의 실용화를 위해서는 기상 관측밀도가 낮은 광범위한 작물 생육지역을 대상으로 일별 기상요소에 대한 공간분포를 추정해야 한다. 이러한 취지에서 본 연구는 미관측 지점을 포함하는 우리 나라 전국을 대상으로 작물모형의 구동에 필요한 최소 기상요소들 중에서 일 최고 및 일 최저기온의 공간적인 분포를 추정하고 그 추정 정도를 검증하고자 하였다. 이를 이해 먼저 58개 지점의 23년간 실측 기온자료로부터 지형기후학적 방법에 의하여 격자단위의 월별 기온평년값을 추정하고, 조화해석법에 의하여 일별값으로 변환하였다. 66개 기상청 관측소에서 수집된 임의 날짜의 최고/최저기온값과 관측소 해당 격자점의 평년값간 편차를 구한 다음, 미관측 격자점을 포함하는 한반도 전역의 기온편차를 거리역산가중법에 의하여 내삽.추정하였다. 각 격자점의 최종적인 기온 추정값은 기온 평년값에 이 편차를 더함으로써 얻었다. 얻어진 온도 분포는 위성자료로부터 추정한 지표온도분포 양상과 크게 다르지 않았다. 300여개의 자동기상관측 장비들로부터 수집된 자료와 비교한 결과, 추정오차는 $1.5^{\circ}C$~2.5$^{\circ}C$였다.

• 환경영향평가
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• 제18권6호
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• pp.321-330
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• 2009

Spatiotemporal changes in the thermal environment in a large city, Seoul, Korea were analyzed using a thermal index, perceived temperature (PT), to standardize the weather conditions. PT is a standard index for the thermal balance of human beings in thermophysiological environment. For the analysis of PT, the data from long-term monitoring and intensive observations in and around the inner-city stream called 'Cheonggye' in Seoul, were compared with a reference data from the Seoul weather station. Long-term data were monitored by installing two automatic weather stations at 66m (S1) and 173m (S2) away from the center of the stream. Through the analysis of the data during the summer of 2006 and intensive observation periods, it was revealed that the stream's effects on the PT extended up to the distance of the S1 site. In winter, the increase of the PT between pre- and post-restoration was stronger at S1, which was nearer than S2 from the stream. These results suggest that PT can be used as an effective model in analyzing the changes of the thermal environment in relation with the changes of water surface areas.